Quick detection of subsoil liquefaction using accelerograms

Abstract:

Soil liquefaction is one major type of secondary hazards induced by earthquakes. Nonlinear soil behavior and pore water pressure generation and dissipation of liquefied subsoils can affect the surface ground motions. In this work, an accelerogram-based method is developed and validated for the quick detection of liquefaction occurrence based on surface ground motion records. Two frequency-related ground motion indices, termed RL and MIFr, are defined and extracted from accelerograms using time-frequency analyses. RL and MIFr indicate the richness of the low-frequency components and the temporal variation rate of the mean instantaneous frequency in the ground motion records, respectively. A new liquefaction database consisting of ground motion stations with both ground motion records and the corresponding liquefaction observations is compiled. Logistic regression is used to develop a new liquefaction classification model that takes RL and MIFr as inputs and calculates a liquefaction indicator (LQI) that can be used to assess liquefaction occurrence. The performance of the proposed method is evaluated and compared with existing accelerogram-based liquefaction assessment methods using a common database, and the method is further validated using a new liquefaction dataset. The proposed method demonstrated superior performance, with an overall accuracy of 92.8% for the common dataset. The proposed method has promising potentials for applications in real-time disaster mitigation systems and rapid post-earthquake loss estimations.